The DOI matches its Crossref record; 16 of the 17 references it cites were found in a registry or an index.
Machine learning for environmental monitoring
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change and environmental monitoring.”
From Artificial intelligence, systemic risks, and sustainability (2021) · cites this paper as [27]
Citations
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
(2016) · Cited by 2,334
Machine Learning: An Applied Econometric Approach
Mullainathan, S., & Spiess, J. (2017) · Journal of Economic Perspectives · doi:10.1257/jep.31.2.87 · Cited by 1,989
Human Decisions and Machine Predictions
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018) · The Quarterly Journal of Economics · doi:10.1093/qje/qjx032 · Cited by 1,040
Cognitive Biases and Heuristics in Medical Decision Making
Blumenthal-Barby, J. S. S., & Krieger, H. (2014) · Medical Decision Making · doi:10.1177/0272989x14547740 · Cited by 598
Kleinberg, J., Ludwig, J., Mullainathan, S., & Obermeyer, Z. (2015) · American Economic Review · doi:10.1257/aer.p20151023 · Cited by 584
Beyond prediction: using big data for policy problems
Athey, S. (2017) · Science · doi:10.1126/science.aal4321 · Cited by 575
An introduction to statistical finance
Bouchaud, J. (2002) · Physica A Statistical Mechanics and its Applications · doi:10.1016/s0378-4371(02)01039-7 · Cited by 355
Enforcement and over-compliance
Shimshack, J. P., & Ward, M. (2007) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2007.05.003 · Cited by 207
Research works printed but not linked: 1
- Zliobaite, I. Fairness-aware machine learning: a perspective. Preprint at https://arxiv.org/abs/1708.00754 (2017). · arXiv
Cited by
Sorted by citations
Our future in the Anthropocene biosphere
Folke, C., Polasky, S., Rockström, J., Galaz, V., Westley, F. R., Lamont, M., Scheffer, M., Österblom, H., Carpenter, S. R., Chapin, F. S., et al. (2021) · AMBIO · doi:10.1007/s13280-021-01544-8 · Cited by 863
Artificial intelligence, systemic risks, and sustainability
Galaz, V., Centeno, M. A., Callahan, P. W., Causevic, A., Patterson, T., Brass, I., Baum, S., Farber, D., Fischer, J., Garcia, D., et al. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101741 · Cited by 497
“Examples include AI applications in climate and Earth system modeling [25,26]; AI-augmented environmental monitoring [27]; autonomous underwater marine conservation interventions and data collection [28,29]; AI-supported tracking of illegal wildlife trade [30]; and “ smart ” urban planning for…”
BackgroundMachine learning for hydrologic sciences: An introductory overview
Xu, T., & Liang, F. (2021) · Wiley Interdisciplinary Reviews Water · doi:10.1002/wat2.1533 · Cited by 292
“…has been used in environmental monitoring applications such as predicting recreational water quality advisories (Brooks et al., 2016), estimating groundwater nitrate concentration (Nolan et al., 2015), and identifying facilities likely to violate environmental regulations (Hino et al., 2018).”
Fascista, A. (2022) · Sensors · doi:10.3390/s22051824 · Cited by 277
“As a fundamental enabler for most monitoring tasks, predictive analytics are required to combine big data and machine learning/deep learning and predict future evolution and impacts of environmental phenomena using both data-driven and model-based approaches [450].”
BackgroundRole of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions
Bhaiyya, M. L., Panigrahi, D., Rewatkar, P., & Haick, H. (2024) · ACS Sensors · doi:10.1021/acssensors.4c01582 · Cited by 251
“12,13 This enhanced sensitivity is essential for the early detection of diseases, enabling medical professionals to identify issues at the best moment for intervention.”
Background
Metadata
- Authors
- Hino, M., Benami, E., & Brooks, N.
- Affiliations
- Stanford University (US)
- Corresponding author
- Benami, E.
- Venue
- Nature Sustainability
- Published
- 2018-10-01
- Volume
- 1
- Issue
- 10
- Pages
- 583-588
- ISSN
- 2398-9629 (ISSN-L)
- OpenAlex
- W2894463230
- Cited by
- 201
- References
- 17
- Citations by year
- 2026: 27 · 2025: 55 · 2024: 41 · 2023: 22 · 2022: 19 · 2021: 16 · 2020: 8 · 2019: 11 · 2018: 1
- FWCI
- 15.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Sustainability (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Public Administration › Regulation and Compliance Studies
- Social Sciences › Law › Artificial Intelligence in Law
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- environmental law enforcement, Clean Water Act, resource allocation, gaming the system, regulatory compliance, environmental monitoring, big data, predictive analytics, Environmental Protection Agency
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